Senior Data Scientist

Remote

Full-time

Job Description

WHO WE ARE

At Trustly, we're building a smarter, faster, and more secure financial future by revolutionizing the world of payments. As a global leader in Open Banking Payments, we are establishing Pay by Bank as the new standard at checkout, providing unparalleled freedom, speed, and ease to millions of consumers and merchants worldwide.

Our Ambition: To build the world’s most disruptive payment network and redefine what the payment experience should feel like.

Trustly is a global team of innovators, collaborators, and doers. If you are driven by a strong sense of purpose and thrive in a dynamic, entrepreneurial, and high-growth environment, join us and be part of a team that’s transforming the way the world pays.

About the team:

The Risk team is responsible for creating and maintaining risk controls at Trustly, developing machine learning models and data analysis aiming to mitigate risk. Our mission is to create a framework and infrastructure to manage risk and create long term competitive differentiation and value for Trustly.

What you will do:

Develop new novel and state of the art AI/machine learning models to support risk strategies;

Recommend data-driven, risk-based business decisions to positively impact KPIs across Trustly's payment portfolio;

Conduct analysis to measure model performance, compare performance across multiple models, and influence model strategy and selection decisions;

Collaborate with ML Engineers to deploy AI/ML models and strategies in Trustly's decision engine;

Explore raw source data, feature research and engineering, supporting decision capabilities;

Support development and maintenance of risk modeling infrastructure, working closely with ML Engineers and ML Ops;

Develop data and business-driven risk prevention rules and strategies;

Monitor risk and decisions trends and performances, provide ongoing optimization adjustments as needed.

Who you are:

University degree in mathematics, statistics, data science or another comparable field of study;

Experience with Data Science/Machine Learning and AI;

Experience developing statistical/machine learning/AI models and experiments;

Risk experience in financial services, fintech or similar industry;

Advanced skills in Python and SQL – Spark and Javascript also nice to have;

Understanding of feature engineering and model development life cycle;

Must have solid English skills to be able to communicate with English-speaking business stakeholders;

Our perks and benefits:

Bradesco health and dental plan, for you and your dependents, with no co-payment cost;

Life insurance with differentiated coverage;

Meal voucher and supermarket voucher;

Home Office Allowance;

Wellhub - Platform that gives access to spaces for physical activities and online classes;

Trustly Club - Discount at educational institutions and partner stores;

English Program - Online group classes with a private teacher;

Extended maternity and paternity leave;

Birthday Off;

Flexible hours/Home Office - our culture is remote-first! You can work in every city in Brazil;

Welcome Kit - We work with Apple equipment (Macbook Pro, iPhone) and we send many more treats! Spoiler alert: Equipment can be purchased by you according to internal criteria!;

Annual premium - As a member of our team, you are eligible to receive an annual bonus, at the company's discretion, based on the achievement of our KPIs and individual performance;

Referral Program - If you refer a candidate and we hire the person, you will receive a reward for that!

#LIRemote

Check out our Glassdoor or our Brazil Life page on LinkedIn for more details about Brazil, our culture, and much more.

At Trustly, we embrace and celebrate diversity of all forms and the value it brings to our employees and customers. We are proud and committed to being an Equal Opportunity Employer and believe an open and inclusive environment enables people to do their best work. All decisions regarding hiring, advancement, and any other aspects of employment are made solely on the basis of qualifications, merit, and business need.

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